Document user personas

docusaurus-docs/community/design/index.md

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+---
+sidebar_position: 5
+description: UI, UX, and graphic design docs
+---
+
+# Design
+
+import DocCardList from '@theme/DocCardList';
+import {useCurrentSidebarCategory} from '@docusaurus/theme-common';
+
+<DocCardList items={useCurrentSidebarCategory().items}/>

docusaurus-docs/community/design/user-personas.md

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+---
+description: Describes current and potential conda-store users`
+---
+
+# User groups and personas
+
+The personas used for informing user research studies and future improvements to conda-store.
+
+## User groups 🏘️
+
+At a high-level, there are two key user groups:
+
+- **General user:** Create, edit, use environments for their day-to-day work
+- **Admin user:** In addition to the general use-case mentioned above, admin users also **setup** conda-store for their team, create various namespaces, add/update users and their permissions, set default packages/versions for their team, etc.
+
+## User personas 🙋🏽‍♀️
+
+### User: Alia
+
+| Role | Reports to | User group|
+|-------|-------|-------|
+Staff Data Scientist | Head of Data Science | General |
+
+#### User story
+
+I want to quickly create a stable and reproducible environment for analyzing data and creating dashboards that I can share with my team to verify and build on my work.
+
+#### Tools they need to do their job
+
+- Libraries - data reader/writer (arrow), data processing (pandas), numerical computing (NumPy), ML (XGboost / PyTorch), Data Visualization and dashboarding (Matplotlib / Streamlit), job schedulers (Airflow)
+- IDE - JupyterLab/Notebook (hence, extensions)
+- Platform - Local computer, organization's JupyterHub on Cloud platform (potentially Nebari)
+- Miscellaneous - Git, GitHub, conda
+
+#### Journey with conda-store
+
+- Discovery:
+    - Team already uses it
+    - Team leader sets it up for everyone
+- Onboarding:
+    - A team member gives them a walkthrough
+    - Documented tutorials
+    - Intuitiveness of the UI
+- General Use:
+    - Environment creation from GUI, YAML, Lockfile
+    - Version control
+    - Using the environment in Jupyter Notebook (local / cloud)
+    - Ability to use any package/version out there
+    - Access to special conda channels
+    - Environments for GPU-powered data analysis and modelling
+- Collaboration:
+    - Share environment with colleagues with a URL (Part of 1-2 shared namespaces)
+    - Fork/Copy environments between namespaces
+    - Download artifacts like docker images for use in other (prod?) machines
+- Troubleshooting:
+    - Understand errors through the error message displayed
+    - Look at conda-store’s documentation & GH issues/discussions, search for the error
+    - Contact team-members or internal support
+    - Open an issue/discussion on GitHub
+
+#### Pain points or biggest challenges
+
+- Environments need to be compliant with company standards, for example, approved conda channels and approved package versions
+- Build environments with libraries from internal mirrors
+- Ensure stable environments that are quickly reproducible by colleagues and can be used by Ops teams for deployment (often on similar machines and operating-systems)
+
+#### Core needs
+
+- Intuitive and fast environment creation & sharing
+- Promise of stability, security, and compliance
+
+### User: Dani
+
+| Role | Reports to | User group|
+|-------|-------|-------|
+Research Scientist and Coordinator | PI | Admin |
+
+#### User story
+
+As a research coordinator, I manage the logistics and admin-tasks of multiple research projects, ensuring that the tools/dependencies used are accessible, reproducible and standardized across projects.
+
+#### Tools they need to do their job
+
+In addition to Alia’s tools, cloud or High Performance Computing (HPC) tools (for example, Google Cloud Platform's web interface and CLI tools.)
+
+#### Journey with conda-store
+
+- Discovery:
+    - OSS Community, conferences, peer suggestions
+    - Tries out conda-store locally and finds it useful
+- Onboarding:
+    - Documentation, self-exploration
+- General Use:
+    - Setup and deployment using the conda-store docs, within current Lab infra
+    - Add team members, create default namespaces and environments, referring to the documentation
+    - Onboard team members to the tool with demonstrations
+    - Track and limit resource utilization
+- Collaboration:
+    - Uses environments created by colleagues to verify their work
+- Troubleshooting:
+    - Documentation, issue tracker (reach out to the conda-store dev team)
+
+#### Pain points or biggest challenges
+
+- Facilitating reproducible environment sharing within teams by setting up relevant infrastructure
+- Managing and supporting team-members (like Alia)
+- May not have DevOps expertise to setup and manage conda-store for the team
+- Reliable environments with guardrails for people new to software development principles (example, not comfortable with YAML spec)
+- Sharing environments widely, considering different operating systems and infrastructures.
+
+#### Core needs
+
+- Setting up & managing packaging infrastructure for the lab, potentially on an HPC system as as non-devops professional
+- Visibility into groups’ package requirements and resources used
+- Sharing environments widely, considering different operating systems and infrastructures
+
+### User: Emma
+
+| Role | Reports to | User group|
+|-------|-------|-------|
+Freelance data scientist | - | General |
+
+#### User story
+
+I want to manage my local conda environments, so that I can be more efficient in my day-to-day work.
+
+#### Tools they need to do their job
+
+Same as Alia, but primarily for individual work.
+
+#### Journey with conda-store
+
+- Discovery
+    - Internet, community spaces, conferences
+- Onboarding
+    - Documentation
+- General Use
+    - Install and setup conda-store locally
+    - Create environments in my personal namespace
+    - Use the environments in Jupyter Notebooks
+- Collaboration
+    - Share relevant artifacts (e.g., Lockfiles) with clients
+- Troubleshooting
+    - Documentation, issue tracker
+
+#### Pain points or biggest challenges
+
+- Sometimes conda environments break while working, adding overhead
+- Environments are not always reproducible when I share them
+- Using the environment-creation artifacts  shared with the application should be as easy as possible (think installers/executables)
+
+#### Core needs
+
+- Reliable and quick environment creation that follow conda best practices
+- Creating reproducible environments that I can share with clients later
+
+### User: Ginny
+
+| Role | Reports to | User group|
+|-------|-------|-------|
+Head of Data Science | CTO | Admin |
+
+#### User story
+
+I need to oversee the implementation, management, and adoption of tools like conda-store to ensure our teams’ workflows are efficient and our data science initiatives align with business goals.
+
+#### Tools they need to do their job
+
+The IDEs, platform, miscellaneous tools used by Alia, primarily for reviews and tracking work.
+
+#### Journey with conda-store
+
+- Discovery:
+    - Team lead pitches it
+    - Community spaces
+- Onboarding:
+    - Team lead/member who sets up conda-store helps them onboard
+    - Documentation
+- General Use:
+    - Review resource utilization
+    - Review package and channel requests
+
+#### Pain points or biggest challenges
+
+- Strategic alignment with organization goals
+- Tool adoption across teams
+
+#### Core needs
+
+- Oversight on tool efficiency and team productivity
+- Enablement of various teams